|
|
Absolute deviation, 绝对离差4 v: D2 d) Z& L5 A, \
Absolute number, 绝对数
. b& w* R. k4 B3 d# wAbsolute residuals, 绝对残差 q( A7 W" u; N1 r- y
Acceleration array, 加速度立体阵: B( H- F+ F/ q8 E
Acceleration in an arbitrary direction, 任意方向上的加速度
% w: Q& |& }; Q# K: h/ Z# m$ fAcceleration normal, 法向加速度" |6 N5 @4 E8 ^. a
Acceleration space dimension, 加速度空间的维数$ Z9 ]; Q8 D4 m+ x( G
Acceleration tangential, 切向加速度
+ V" f5 i0 |9 X/ u$ ]: p! ]Acceleration vector, 加速度向量
- J! e: o; o6 G/ c/ oAcceptable hypothesis, 可接受假设% e/ r7 L+ N' L8 B9 u- R' n
Accumulation, 累积0 m3 G3 ^4 Q* ^3 Z& A% k
Accuracy, 准确度' W* W2 `+ U+ j; o. K5 s
Actual frequency, 实际频数
) W$ u% z# I: V- BAdaptive estimator, 自适应估计量
8 X7 Q5 n% A4 v" p$ D$ pAddition, 相加
2 k8 Q% X S- O$ PAddition theorem, 加法定理5 B: m. o b: D
Additivity, 可加性+ W# e/ i, A2 r3 A
Adjusted rate, 调整率- x0 n4 @, L9 d6 g2 [4 B( ~
Adjusted value, 校正值1 \( F2 A& k0 O# O/ K- F K
Admissible error, 容许误差0 E2 [" \5 u1 _! M: x1 J
Aggregation, 聚集性
# i( c3 q$ j8 e2 S2 `9 P Q4 T1 oAlternative hypothesis, 备择假设, @6 S! I1 `. Y" X
Among groups, 组间( ]4 N( I5 i9 ]' h! J Q+ ^, |
Amounts, 总量$ W& X- d |" n$ w6 x
Analysis of correlation, 相关分析
4 f% c8 M1 F$ i$ QAnalysis of covariance, 协方差分析 D2 R# S! D) ~9 M+ O+ P' y
Analysis of regression, 回归分析
, j$ L' @% p6 z/ {, h' eAnalysis of time series, 时间序列分析* Z( d- y& e0 S' ]& |* {4 Z; K
Analysis of variance, 方差分析: D, u, M e1 N+ Y+ ~0 \2 \
Angular transformation, 角转换
& P; C* U5 d* O1 p8 k! wANOVA （analysis of variance）, 方差分析# t# y T% E2 d" L- R+ f
ANOVA Models, 方差分析模型
+ o4 }. w3 s# \$ X$ f* w9 a0 CArcing, 弧/弧旋
) ]. E( i! y8 p# g0 l, UArcsine transformation, 反正弦变换
( a# X3 z; `( [6 J' uArea under the curve, 曲线面积
7 x2 ]# @5 j5 yAREG , 评估从一个时间点到下一个时间点回归相关时的误差 B) s; }. I& V( j
ARIMA, 季节和非季节性单变量模型的极大似然估计 % L% f3 V: e: N% O3 T8 W& r6 s
Arithmetic grid paper, 算术格纸
- n4 t- Y! M& `2 q/ b8 x JArithmetic mean, 算术平均数% s" n/ d$ L! f: z" L4 r
Arrhenius relation, 艾恩尼斯关系+ V5 C+ K/ i& g/ E7 b" K
Assessing fit, 拟合的评估
; l& _ `7 g! iAssociative laws, 结合律* R; F. w" n6 \. [1 S1 |* q
Asymmetric distribution, 非对称分布$ s( P) D G p9 n |
Asymptotic bias, 渐近偏倚3 g2 w9 [; j( R0 z% m
Asymptotic efficiency, 渐近效率
9 `6 U+ A# D( ^8 zAsymptotic variance, 渐近方差
' ]0 n9 Q+ B2 }; E# t9 }, cAttributable risk, 归因危险度
% I" @* g: o z/ MAttribute data, 属性资料6 l) y: z' Q, W, }7 }
Attribution, 属性. ~( D# |0 @! x( O* v* U0 N; {
Autocorrelation, 自相关
. d( v6 B, h9 l) N5 z: h! ?1 }- u: ~, oAutocorrelation of residuals, 残差的自相关$ A- r& m2 ^. ^9 E
Average, 平均数6 M, C# k8 Y$ u5 r2 }; {9 ?
Average confidence interval length, 平均置信区间长度! d2 |/ V, A, y4 j. o) B$ r& W
Average growth rate, 平均增长率+ n2 o$ U1 L! z7 g9 Q. I! G$ x
Bar chart, 条形图; T9 r% D( o$ q9 [2 ^8 u4 ?& B& ?
Bar graph, 条形图# `/ U2 `# K0 B# z, X+ @
Base period, 基期
8 e$ x: E9 V& J4 R( DBayes' theorem , Bayes定理
8 Y3 r* r& Z+ Q: q8 eBell-shaped curve, 钟形曲线
& e4 B! m& k7 `6 i+ M/ b; LBernoulli distribution, 伯努力分布" _. Z: d' J' G. C+ `1 }6 o
Best-trim estimator, 最好切尾估计量
+ J& X' l, p' t2 Y" B4 h" x& p" XBias, 偏性9 ~! R8 B, Q. |" Q& m$ W
Binary logistic regression, 二元逻辑斯蒂回归
0 U# Y+ A% R3 OBinomial distribution, 二项分布# ]9 {7 N; [: e3 U8 x1 `5 _# w/ Q6 F/ [8 Y
Bisquare, 双平方1 X- e& B1 b3 x. g
Bivariate Correlate, 二变量相关
) u6 \1 e$ M8 c8 aBivariate normal distribution, 双变量正态分布
& g9 C& T2 G8 w' [9 TBivariate normal population, 双变量正态总体; J& M; a) v0 q5 Y* g3 ^. u% X
Biweight interval, 双权区间
5 p D9 P3 F# L9 \ H/ ~# v6 f$ GBiweight M-estimator, 双权M估计量
6 y* H0 h8 [7 p& [( P5 hBlock, 区组/配伍组
3 N9 j3 e5 r6 o! o1 n" B: O! O- GBMDP(Biomedical computer programs), BMDP统计软件包( p: \, B# R; T5 J. J6 L3 ~
Boxplots, 箱线图/箱尾图* q$ c0 O6 U% L- m* l! T5 h
Breakdown bound, 崩溃界/崩溃点2 y! q& U2 w4 T; o6 i& Y
Canonical correlation, 典型相关
8 O0 ~. Z4 J: s% M" SCaption, 纵标目
+ v4 N4 s4 P9 J7 f, gCase-control study, 病例对照研究
" v5 p: b- M ?$ A/ { MCategorical variable, 分类变量
6 X$ [: k" Z* t, U: jCatenary, 悬链线 [, ?& }) \! W" z4 b$ u* h. O
Cauchy distribution, 柯西分布( ~3 j( |4 v; u4 _4 q, Y; g) _
Cause-and-effect relationship, 因果关系8 `) t" I7 `7 v! o
Cell, 单元
; ~; G. m" l- W; i+ M/ K1 WCensoring, 终检
% }$ h1 y z& r3 Q) V0 } {6 `Center of symmetry, 对称中心1 J# a4 B6 _# e9 Y- V
Centering and scaling, 中心化和定标
8 t0 D4 M7 w2 A& P6 l6 H. jCentral tendency, 集中趋势8 D+ a2 v, h4 F9 r/ y' S9 O
Central value, 中心值7 m8 ?8 j* X0 s' d5 m0 c
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
# f- t! q" \0 w; _; ^, l, WChance, 机遇
; Y: B: K' V) P0 FChance error, 随机误差- g1 h& ]4 j, i
Chance variable, 随机变量( k( r- u6 A' ^, c' V, }" F/ \2 Y9 `+ a1 }
Characteristic equation, 特征方程
# N8 E# k' t1 E, \" D" OCharacteristic root, 特征根2 l6 i% P/ Z3 H# h: M; ^$ J
Characteristic vector, 特征向量/ u' N+ S2 ]) U% ^
Chebshev criterion of fit, 拟合的切比雪夫准则
( U% G8 ^8 [5 g0 C( F$ ?Chernoff faces, 切尔诺夫脸谱图
! g; a$ R) b( ?+ J# @, tChi-square test, 卡方检验/χ2检验6 W* z/ t& f, K5 _) C
Choleskey decomposition, 乔洛斯基分解
. z$ m5 a" D; n( T9 \Circle chart, 圆图
) L7 i% A! R% S* I( ~; iClass interval, 组距
4 P+ O( f. C+ J" z) w. EClass mid-value, 组中值+ v1 [) W' k, ^$ D* u1 ]% O- K
Class upper limit, 组上限
* Z% q- ~9 p8 h9 Y9 t6 ^& xClassified variable, 分类变量
+ s) |5 U' m, H! @Cluster analysis, 聚类分析
1 k) H. ^& S. T% `, _Cluster sampling, 整群抽样: ? a, _7 X( p$ o4 x
Code, 代码
3 b8 L* W) p u# O5 y( dCoded data, 编码数据5 R _( e) Z g7 r! L c
Coding, 编码
8 H2 s- b5 x C. ^" W) bCoefficient of contingency, 列联系数+ W5 i$ Q+ z a: f; K- {/ Y6 }. T
Coefficient of determination, 决定系数% R/ H" r g7 M# P) p' z
Coefficient of multiple correlation, 多重相关系数7 O6 ]* U# H- v" t" ?- o9 J
Coefficient of partial correlation, 偏相关系数
! @# s) _; t {+ W' c( hCoefficient of production-moment correlation, 积差相关系数
5 v2 k$ } k) a* P% q2 [Coefficient of rank correlation, 等级相关系数! h) P: i1 N; G3 w) g! |( w' n
Coefficient of regression, 回归系数2 [# c, S+ n8 @1 H7 i5 Z/ o
Coefficient of skewness, 偏度系数0 M* S; n! w5 g! O# _
Coefficient of variation, 变异系数
; H. A7 `" a0 c6 RCohort study, 队列研究: _' R0 h5 k t# S4 b& X
Column, 列
) b! d% Q. a: JColumn effect, 列效应
9 \4 R8 t; B" W6 h5 b' D4 RColumn factor, 列因素7 \' {9 f! W, o, N5 c3 m
Combination pool, 合并; A0 C, v$ s- K6 t3 ~ Y5 P- g
Combinative table, 组合表
4 e5 K& Q4 `5 v( r( T4 GCommon factor, 共性因子
+ {$ b% @7 t3 n4 f9 _$ mCommon regression coefficient, 公共回归系数
3 c: z8 {/ ^! r, JCommon value, 共同值. s, T( S/ C: @# ^* e+ w
Common variance, 公共方差
% j3 k8 e/ \* s9 L- R7 g6 dCommon variation, 公共变异
% P2 e' \ m+ }9 @9 F3 d; S5 m3 \Communality variance, 共性方差) x1 j+ E$ f! n9 o# K1 I
Comparability, 可比性
( M) z1 f a7 i% l8 D2 ZComparison of bathes, 批比较
( `6 n- [ H9 \Comparison value, 比较值% B; ^! c& J% Y" e% Y& c$ m2 Z
Compartment model, 分部模型1 h5 m& i8 i% R8 I. w. x2 }" N
Compassion, 伸缩3 _7 n# I: K# i2 N$ ]/ I
Complement of an event, 补事件" |5 A7 Y4 \; H7 H: f
Complete association, 完全正相关
& H' [( o1 ~6 c( |% {9 n9 UComplete dissociation, 完全不相关
1 u" l% Z: k6 f# F5 J, R$ I$ XComplete statistics, 完备统计量
; J# I, U$ F2 F5 E; ^3 O7 jCompletely randomized design, 完全随机化设计
( N! D* Q8 K7 w9 U, Q- FComposite event, 联合事件7 K( c5 j, @. D. }, Y% \* ?
Composite events, 复合事件
" Q6 z1 x% ~+ q7 qConcavity, 凹性
9 q, Y* |9 r8 U& _" N( _Conditional expectation, 条件期望
9 X s5 Q! u, n! rConditional likelihood, 条件似然
1 h3 ]7 k/ U6 F$ J+ C* o( i4 _; \Conditional probability, 条件概率( A4 P5 Q9 L3 _' x8 E% n. e
Conditionally linear, 依条件线性
6 T: H" q5 _/ B7 l# }Confidence interval, 置信区间
5 u3 j- ~* x4 ]2 k4 @2 RConfidence limit, 置信限
8 y. @6 P" D- a; }3 NConfidence lower limit, 置信下限
% Q1 K" W. s: O5 L0 [Confidence upper limit, 置信上限
& z' _1 G) i* F _! [4 G2 G1 fConfirmatory Factor Analysis , 验证性因子分析
7 k! l4 l5 h+ E% L% HConfirmatory research, 证实性实验研究4 N0 ^' h+ ~; O5 @7 d2 B
Confounding factor, 混杂因素
3 a e7 m6 Y. U- C0 L1 OConjoint, 联合分析# }6 I0 ~2 Z* `8 D7 n2 f5 d( w( Z& p
Consistency, 相合性 j: g0 A: ` {
Consistency check, 一致性检验. e& c$ c" O" Q1 M" ^% c
Consistent asymptotically normal estimate, 相合渐近正态估计
y8 x. M- H( l. {8 p$ x& \3 Z- sConsistent estimate, 相合估计' B2 @1 C# d# }9 n3 r
Constrained nonlinear regression, 受约束非线性回归4 j1 ]% a$ p$ u0 S F) w
Constraint, 约束
1 T. G+ H$ @( S' n3 \Contaminated distribution, 污染分布
; q( i$ ]. [: _- w) p F, s( v' IContaminated Gausssian, 污染高斯分布
U, `& O9 s: ^* @! @Contaminated normal distribution, 污染正态分布
$ p4 U% X1 S, O8 L3 E$ l+ xContamination, 污染
4 p6 `4 k& J- N% o7 y( rContamination model, 污染模型
. @6 l/ E0 S7 d' a; N, g5 u: xContingency table, 列联表
3 s' B2 C0 Z: dContour, 边界线
/ I2 s) L+ O% N1 KContribution rate, 贡献率
4 i! X7 p3 e& tControl, 对照
% C& u' x; g% z% Q+ W% L& `Controlled experiments, 对照实验
0 K1 H0 r. e' J8 I! c s5 KConventional depth, 常规深度
) }1 x+ G: R" W3 UConvolution, 卷积1 R/ h+ i% u% m/ w8 |
Corrected factor, 校正因子
# d( }4 F4 R8 [+ k# E! @ hCorrected mean, 校正均值0 z# ^! N, w9 O3 G8 `$ r" O
Correction coefficient, 校正系数
! {% R4 N9 s0 k+ |* \/ W: qCorrectness, 正确性
+ N4 E& y) R1 y+ Z: ICorrelation coefficient, 相关系数
0 @8 m/ {8 Z" O$ _5 c8 b% SCorrelation index, 相关指数; ? Q: O+ U) C' L, e
Correspondence, 对应6 F _& I% E0 V( u! {, ]
Counting, 计数
# u0 x, V: V6 tCounts, 计数/频数
# L1 g' }( `" hCovariance, 协方差; [# j) ~. C$ w n9 T2 _
Covariant, 共变
1 x! K( P5 \9 i3 @6 N# x- U$ CCox Regression, Cox回归1 }+ p0 i' v. r0 `5 z1 s8 }3 V
Criteria for fitting, 拟合准则
) s0 h9 n6 I; A3 @Criteria of least squares, 最小二乘准则
3 Q( N/ q; q. sCritical ratio, 临界比: C8 G& ~' s: e) W5 G% }& V
Critical region, 拒绝域
3 O; @+ d( h- kCritical value, 临界值
3 m, Z) {) q! ~6 H5 J7 DCross-over design, 交叉设计6 d# @4 l+ Z, N, @+ y
Cross-section analysis, 横断面分析# @1 O$ }- G X0 `- u* m
Cross-section survey, 横断面调查
0 I8 a, s$ F6 G ]7 QCrosstabs , 交叉表
% k; W+ k1 M! v- {0 b, P: xCross-tabulation table, 复合表* t) e9 m; D' ^
Cube root, 立方根$ Z) l8 b, [7 [2 Q# H, Q
Cumulative distribution function, 分布函数. r. f5 f, Z2 b$ e+ U/ ?- Y( [
Cumulative probability, 累计概率+ _# N$ V+ }9 Q. i" v
Curvature, 曲率/弯曲% p+ S$ r5 G# ]9 e7 |4 K0 j; w
Curvature, 曲率7 ]. u5 e5 d' N% e) q, Y
Curve fit , 曲线拟和 $ U7 F+ Q- n7 h! m% B, C* C
Curve fitting, 曲线拟合' k. {+ K1 p/ [8 V
Curvilinear regression, 曲线回归: n+ d6 _6 o& J# U$ E
Curvilinear relation, 曲线关系
7 j6 ^" u" y; w8 N- U; wCut-and-try method, 尝试法
+ p- f; n, g( ?# E8 f) b2 JCycle, 周期3 \1 l) z" E8 m
Cyclist, 周期性4 ^, n( B* r) F$ }6 |
D test, D检验
2 [3 e; g: `+ ]0 mData acquisition, 资料收集
) B" E" n2 U8 `* q8 DData bank, 数据库! {& Z) F3 a4 s' F3 z3 U0 U$ Y
Data capacity, 数据容量
2 \# D9 j9 t* c) M7 EData deficiencies, 数据缺乏
{1 i" _4 C# z/ }* p: {9 oData handling, 数据处理
- |7 s; A+ K3 ^Data manipulation, 数据处理9 D4 L m% p# B6 L* D& P: C. u1 V
Data processing, 数据处理
1 E4 h0 _9 f# ?" mData reduction, 数据缩减# q/ Q/ j* b4 A, ?9 a
Data set, 数据集# F9 }1 ? Y# o0 _, Q- t
Data sources, 数据来源+ Z, P' L5 ~$ ` m9 f
Data transformation, 数据变换7 k) W$ j7 A9 [, B
Data validity, 数据有效性, A* j) i% J$ b5 K1 G
Data-in, 数据输入
3 Z' `7 ^+ C" T0 t2 J" nData-out, 数据输出* d; l0 c0 w$ n
Dead time, 停滞期
- g9 `- B% X0 f: RDegree of freedom, 自由度8 D) y* w0 c" l! |% m5 s+ ]
Degree of precision, 精密度
; f* E; Z a+ D5 DDegree of reliability, 可靠性程度5 i9 _2 Q. w( x% r! P5 O4 y- f
Degression, 递减. b" t8 J' ^! [2 {' q: q9 L* U
Density function, 密度函数0 [: H6 I$ a" q$ m8 X9 Z6 N
Density of data points, 数据点的密度6 G3 d6 g) n0 K- X$ |4 K: j1 n
Dependent variable, 应变量/依变量/因变量
8 I7 g2 o& s' e0 cDependent variable, 因变量
$ u. k: ]. z1 gDepth, 深度) D" ?" q7 N( R' b: h5 j
Derivative matrix, 导数矩阵' I3 x* D% \3 l1 m2 j/ W
Derivative-free methods, 无导数方法
- D" j" f% `5 U3 e: ^Design, 设计
" e. j5 A- v4 i3 b9 ADeterminacy, 确定性* G r. Y2 _+ T
Determinant, 行列式% C3 ?0 w. E* ?1 a% Y4 U1 I
Determinant, 决定因素
) ~! P: x5 n: M2 i8 F4 m: v+ x* QDeviation, 离差
' M8 U3 `: u7 a' w0 D* [: UDeviation from average, 离均差% h- I4 r' _$ R. R2 }
Diagnostic plot, 诊断图1 ]' m* J; \4 J3 Q7 @* D
Dichotomous variable, 二分变量; \* E. W E. i% T0 ]6 e
Differential equation, 微分方程
3 {/ w8 {! f# x$ b9 K2 F7 MDirect standardization, 直接标准化法$ s8 D7 R& K7 R1 l
Discrete variable, 离散型变量, \5 l3 h. ?6 w! P% Y. a9 G
DISCRIMINANT, 判断
& G& s$ P& o, B/ ^- F7 NDiscriminant analysis, 判别分析
- V8 L$ l6 P& XDiscriminant coefficient, 判别系数
9 Z% m# c- Y k8 T8 sDiscriminant function, 判别值
- Y+ [- C0 Z" \* u+ X+ ?Dispersion, 散布/分散度" A$ B) t5 z, ]4 S$ R
Disproportional, 不成比例的* c3 R( V/ h- N `, O
Disproportionate sub-class numbers, 不成比例次级组含量
! e9 I2 f; K- y# Y3 R: E7 sDistribution free, 分布无关性/免分布+ c( h; W( d, C2 d" z% O4 O
Distribution shape, 分布形状/ m. V1 ^% l6 z" y1 |/ c u5 I0 Q
Distribution-free method, 任意分布法1 U G8 V4 A: o u, o) C- j# k* L
Distributive laws, 分配律
% N" j2 V4 f0 @8 Y1 ~Disturbance, 随机扰动项1 _# @+ B9 S5 d1 i8 n
Dose response curve, 剂量反应曲线
- Z/ w0 t# ]( E% s% M, uDouble blind method, 双盲法2 p" S _) _" R& c
Double blind trial, 双盲试验" ~$ n/ d- g% l
Double exponential distribution, 双指数分布
0 z0 v6 J/ k b' o% u6 FDouble logarithmic, 双对数
, L6 r" x% ~, u5 M! |0 UDownward rank, 降秩
1 |8 M: S; p! B2 a& W y, T8 z* eDual-space plot, 对偶空间图. Y$ F7 X- J7 b- k
DUD, 无导数方法
7 S' F5 z8 F0 a. i- H EDuncan's new multiple range method, 新复极差法/Duncan新法7 H8 D4 Y& J/ Z2 W4 z
Effect, 实验效应
+ P4 y4 }) U! U- W9 E! rEigenvalue, 特征值 o5 l1 M* Q, G: x% Z
Eigenvector, 特征向量
/ T. ?$ g1 m+ z: ~/ q0 C% DEllipse, 椭圆2 Q: V$ V ?& N# p/ W
Empirical distribution, 经验分布" W: a! a4 ~: @& Y- S9 j
Empirical probability, 经验概率单位
, f6 ~5 x' r; z& J& oEnumeration data, 计数资料
5 q4 H- f3 ~0 g s# h3 i! Q7 sEqual sun-class number, 相等次级组含量
! A7 K0 O: V' A' u' B) W; eEqually likely, 等可能
8 O& f% B T- p$ j: JEquivariance, 同变性) }& Z* ?8 R3 h. D' g0 b
Error, 误差/错误
4 ?+ E2 G0 d# {; g. CError of estimate, 估计误差% V% g/ ]/ m8 D' |* A- H X- f
Error type I, 第一类错误* Z" W% `- T1 b4 j+ b# b! B' p
Error type II, 第二类错误
' n( \0 c" P. V. L0 D+ LEstimand, 被估量0 z$ {" z% D2 g( s+ t* I
Estimated error mean squares, 估计误差均方5 P3 I! Q/ {: S. Q* `- t; U; ?
Estimated error sum of squares, 估计误差平方和
8 u$ K( P b! T9 W4 ?0 n G q2 PEuclidean distance, 欧式距离! ~3 c9 k6 N' X: b/ M* N5 Y
Event, 事件# i$ `7 X; N: t+ Z8 Z4 O
Event, 事件" C9 ]* ~1 _/ l# d# I
Exceptional data point, 异常数据点: U$ u$ l6 n. p+ a5 h8 X3 _
Expectation plane, 期望平面5 z+ z8 `& l& M/ A$ J$ Z
Expectation surface, 期望曲面
- S3 v# @5 K. |' {5 N1 `/ K! i' MExpected values, 期望值
* A+ D. q( n7 d* tExperiment, 实验0 f7 l- Z' A8 _: R! I7 j
Experimental sampling, 试验抽样
3 s3 P2 q3 K" \: p: H7 k0 z# dExperimental unit, 试验单位: s! s Q# a: W+ g
Explanatory variable, 说明变量6 T8 C* Q: q+ A) [
Exploratory data analysis, 探索性数据分析$ E9 S/ `0 M+ A4 h
Explore Summarize, 探索-摘要, C& T, t8 U' f i9 n" \
Exponential curve, 指数曲线# _/ j2 V G g* q6 B8 U' b- ?
Exponential growth, 指数式增长
3 e) S/ m, e$ q0 pEXSMOOTH, 指数平滑方法
$ U$ a, k- s% H. _, r8 ?2 ?# B- Q( XExtended fit, 扩充拟合
6 Z# `; E; J+ i, ]) LExtra parameter, 附加参数9 B8 S) y j" `7 \ u& ^
Extrapolation, 外推法
& n4 ?0 q# |9 X( YExtreme observation, 末端观测值7 i3 r! G8 o$ w* d* {9 L) J
Extremes, 极端值/极值
" _ n S# @& c/ y T$ E& T1 zF distribution, F分布 X6 `5 {; N9 `; ^/ h3 A
F test, F检验8 T( ~, G# |; j6 M
Factor, 因素/因子4 `3 y/ t8 k @& W8 j0 Z
Factor analysis, 因子分析; E: T, J: `7 s
Factor Analysis, 因子分析
6 _4 H7 i+ C% ^7 n8 R; @+ U4 @* GFactor score, 因子得分
/ [. ]" |1 e: U6 E( t* k. K+ dFactorial, 阶乘% N+ v" w+ d& ~( Q6 q
Factorial design, 析因试验设计# ?& g8 T; J8 ^" k
False negative, 假阴性 v+ N. P% M/ k. T0 g! z. g# X
False negative error, 假阴性错误) }, U& S7 ^; T& B( G# t' U
Family of distributions, 分布族
y U) p' o5 U2 L4 J1 P' AFamily of estimators, 估计量族# X3 d5 ]" n: c
Fanning, 扇面
5 A5 s8 B, Q) [# S/ _0 ^Fatality rate, 病死率* x" d% V" P" ]% ]4 x
Field investigation, 现场调查) A4 i* g3 K& b6 @, q3 p
Field survey, 现场调查% z5 @, J$ z; v9 s* u" c9 Z
Finite population, 有限总体9 \& d# C. g G% \+ m4 C- }6 k
Finite-sample, 有限样本: `7 j. i! w K3 s6 v
First derivative, 一阶导数
) d& x' S- C) z2 U. w+ F! TFirst principal component, 第一主成分' D" u2 M0 R( \" a! \' _! @# `
First quartile, 第一四分位数
/ `, u( ^0 W# n. F" hFisher information, 费雪信息量
9 l7 T' x7 h5 i3 |, E0 n# nFitted value, 拟合值
/ @) p/ K. @$ OFitting a curve, 曲线拟合4 M) Z, G7 F: [
Fixed base, 定基
/ B( _4 \" T2 y* ^0 nFluctuation, 随机起伏" _# y: p: I8 m2 g% X- e+ H' @3 x
Forecast, 预测
, l0 t! {& u$ K) T. Z3 u3 P9 BFour fold table, 四格表
, ?( H& w8 O/ j. aFourth, 四分点
+ w; f! Q4 h/ p- _/ k. aFraction blow, 左侧比率: D/ P2 t# {4 x$ s1 V' ~4 ~7 g
Fractional error, 相对误差
4 V5 l' D4 h9 n6 l4 l; uFrequency, 频率
! R) r1 F* n& z, X" MFrequency polygon, 频数多边图! ]5 a1 Q8 g d# W& W% U
Frontier point, 界限点
) C: E& X# E+ D4 D; o5 @" g1 e' PFunction relationship, 泛函关系* F* L; b& r$ I" b% _, o
Gamma distribution, 伽玛分布
! q; z2 s) g WGauss increment, 高斯增量
" o" P7 C+ Z+ P& W+ hGaussian distribution, 高斯分布/正态分布
0 Y& x5 H6 P" f d- vGauss-Newton increment, 高斯-牛顿增量: _8 B y3 v/ y1 k0 C$ W: J3 t) M
General census, 全面普查' @4 c$ v/ j- w6 x0 {; x5 r* {
GENLOG (Generalized liner models), 广义线性模型 7 ^4 z4 z! r C; n
Geometric mean, 几何平均数! |( G9 A2 j- K
Gini's mean difference, 基尼均差
# ~8 h& r) F: rGLM (General liner models), 一般线性模型
+ G% O/ W3 M3 n1 P. c8 bGoodness of fit, 拟和优度/配合度, N% Q" ]& D/ H# n
Gradient of determinant, 行列式的梯度
6 w5 q A5 R; e q; `, _Graeco-Latin square, 希腊拉丁方
4 R9 U& L: r) o1 B/ W3 WGrand mean, 总均值
- T! V7 m4 N2 Z9 QGross errors, 重大错误
, H8 q- u+ j# e! t; vGross-error sensitivity, 大错敏感度
/ b: V- m: m* E( IGroup averages, 分组平均- E% x% [4 `1 z
Grouped data, 分组资料
/ a( k4 N. V+ JGuessed mean, 假定平均数/ S4 M# A( d; p* M5 |
Half-life, 半衰期
* F, w* E2 c; X, dHampel M-estimators, 汉佩尔M估计量" b& t2 Z4 q" _: _& b+ e( d1 @# t
Happenstance, 偶然事件
, ~/ a/ J$ ?" r/ e* T9 cHarmonic mean, 调和均数. u' J8 P1 v# c/ {0 g5 z0 V# P6 g3 L
Hazard function, 风险均数
8 ^1 {' d" S+ L/ G/ p8 PHazard rate, 风险率% g/ z( V B1 @/ t2 M) s% P a
Heading, 标目
. j4 e- B. q: eHeavy-tailed distribution, 重尾分布
, C+ [! n7 L( P/ {$ `+ HHessian array, 海森立体阵
" L5 T4 G- ~- x6 l* o3 E; rHeterogeneity, 不同质
3 h1 i6 w2 _8 l1 I- \ |; cHeterogeneity of variance, 方差不齐 + K5 }/ K" g; |7 Z; s# P- X
Hierarchical classification, 组内分组9 g/ M5 e) l0 i: a5 C
Hierarchical clustering method, 系统聚类法
) b- N D3 L- Z. A) d. m' S( kHigh-leverage point, 高杠杆率点
9 g- L" T1 N% ~5 rHILOGLINEAR, 多维列联表的层次对数线性模型7 u$ O% Y9 Z$ }, w1 d
Hinge, 折叶点6 }& X g! Y# n% I1 C
Histogram, 直方图$ K @" r( \' _" W+ L* A
Historical cohort study, 历史性队列研究
( ?' l& z. z2 i3 P9 F' HHoles, 空洞/ {+ m2 Z% z% `8 q7 e9 M; `
HOMALS, 多重响应分析8 x- J8 H! _* X
Homogeneity of variance, 方差齐性; N9 s9 \0 n8 S! J. b
Homogeneity test, 齐性检验6 \* ]) u. z, D0 r% s# o! B# |
Huber M-estimators, 休伯M估计量* h$ {9 x5 {7 g( X
Hyperbola, 双曲线& V& Q) w% y* d. N0 p
Hypothesis testing, 假设检验* R8 h2 @8 t- Q- p
Hypothetical universe, 假设总体
0 K2 f4 S u, S8 N. d' w$ _8 D- nImpossible event, 不可能事件
; j% r0 w* x& a& d( ^; CIndependence, 独立性
k0 f6 C" @) p% o+ r3 KIndependent variable, 自变量" X W H/ F/ w1 }6 k/ m
Index, 指标/指数
; R+ {7 W; r7 D. ~+ F1 M0 L) p x+ fIndirect standardization, 间接标准化法5 v% \2 S/ k8 ~7 X7 q
Individual, 个体
5 k) o0 y% E: YInference band, 推断带0 |' ` g7 E, r1 ]
Infinite population, 无限总体* t& Z z E4 S4 i, ^) M
Infinitely great, 无穷大6 O' d' Q$ b, V. p
Infinitely small, 无穷小* @0 P$ B2 i" M% N3 a. ~) s
Influence curve, 影响曲线8 h; w' P# E; Q8 l/ v
Information capacity, 信息容量
4 d% p/ F2 D' @: b6 E% FInitial condition, 初始条件5 A/ j2 ~! U2 ^" B% }6 Z
Initial estimate, 初始估计值. ]- |1 ^/ d. i7 h3 D- V" q& I4 b
Initial level, 最初水平8 y% ^4 t0 _6 e. ^% r" w
Interaction, 交互作用: B1 Q2 q: }0 E4 O
Interaction terms, 交互作用项: N$ y7 B; V8 a: \+ ]; y
Intercept, 截距% ?! S" w0 }* Y# i, l- F# f7 ]
Interpolation, 内插法
7 o' _, T O3 J$ x8 dInterquartile range, 四分位距2 z$ N# k7 R2 n/ d) O! e
Interval estimation, 区间估计' N, x% v/ `* x- P
Intervals of equal probability, 等概率区间
6 M" x4 T2 @2 Y, D J* fIntrinsic curvature, 固有曲率
3 @ L* M. m: i3 K e1 n. [Invariance, 不变性
* i. A0 Y7 ?. H; K& R4 V* N6 { Q! fInverse matrix, 逆矩阵6 E/ O1 g% {8 c# f! `7 A
Inverse probability, 逆概率
) ^+ _3 \) X: s2 ^8 d) TInverse sine transformation, 反正弦变换% W0 Y- L, j. a% |: H ]
Iteration, 迭代 7 Y/ V$ g8 F! a7 _7 Z Q% P* g
Jacobian determinant, 雅可比行列式* D ?1 [8 G; @! @# \; x3 _& j
Joint distribution function, 分布函数
" V. f% `" B6 b7 y. n; j: u8 \Joint probability, 联合概率
* ]7 K8 m- e" ^" f: W, a6 kJoint probability distribution, 联合概率分布
! l& ~1 \& }8 F, mK means method, 逐步聚类法
" c4 K9 b2 K8 A( f# w/ a# ^ ]' XKaplan-Meier, 评估事件的时间长度
: N+ q- o% s* D1 S: r' N9 mKaplan-Merier chart, Kaplan-Merier图
7 C8 P9 U& p; c# e6 lKendall's rank correlation, Kendall等级相关
) X. x7 T. [2 V: uKinetic, 动力学! w" ^* l+ z! b9 D: w* U
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验 v5 J4 g7 N# C5 I. y0 P
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验5 `& b$ o! A' t: v4 W1 O% U
Kurtosis, 峰度! A' H8 T3 t5 y" e. F6 X" l6 I
Lack of fit, 失拟
3 M$ l+ z- k( i8 m; C( Z5 A" `( @) g8 \Ladder of powers, 幂阶梯% k1 Y& x o4 e$ E9 w F2 w8 ?
Lag, 滞后. T4 n5 V5 ]0 U
Large sample, 大样本
% H; ~) x7 ]* r$ c8 ULarge sample test, 大样本检验
; i9 z' U* j i7 @Latin square, 拉丁方% C9 V+ M5 |) U+ h2 s
Latin square design, 拉丁方设计& x9 @5 D& f( B: {8 s# F+ K* K
Leakage, 泄漏
K0 z" s$ h% p, Z4 F9 g2 PLeast favorable configuration, 最不利构形
9 Z" |) f* h7 @; q) fLeast favorable distribution, 最不利分布9 |% W% ^/ ` t( S9 e: D, F
Least significant difference, 最小显著差法7 d6 ]2 `$ @6 P
Least square method, 最小二乘法
* f! N6 b3 A- t+ [) x# GLeast-absolute-residuals estimates, 最小绝对残差估计
$ O4 h% b4 q8 j. U: cLeast-absolute-residuals fit, 最小绝对残差拟合
) E _2 W; d2 |7 R7 x1 l& |) GLeast-absolute-residuals line, 最小绝对残差线2 N3 K, ~4 E- `% @3 F; d
Legend, 图例9 I) x" z* V0 e) {9 b) p/ C4 L
L-estimator, L估计量! x/ ^, w2 T: |! Z& s
L-estimator of location, 位置L估计量
4 s% M! _* S. P' wL-estimator of scale, 尺度L估计量
1 Q- D. m5 n9 Y. a$ ^, h! X& U% TLevel, 水平
: }& H% J$ ^9 l# ]Life expectance, 预期期望寿命
2 b" T q7 b- O5 u" P1 }) T8 lLife table, 寿命表. V" q [( m5 \" X1 N- y& ]! o% _
Life table method, 生命表法
# X( B' f5 B8 u b% E. bLight-tailed distribution, 轻尾分布
, \+ m1 E: B; j) Q( n# Q% NLikelihood function, 似然函数
9 ^% r6 p8 m7 q" F- ILikelihood ratio, 似然比8 v* y+ H0 R# ~
line graph, 线图9 B4 c! n) {) t9 P- |8 X' a
Linear correlation, 直线相关# X# S* K' {. f' K7 u, Q' c& F
Linear equation, 线性方程
1 C. Z1 |! n% f- p$ ?Linear programming, 线性规划
, N, k5 _4 t5 O7 s7 L* B. ELinear regression, 直线回归+ V$ ^1 ^0 J- e2 R. s: s' B, W( W
Linear Regression, 线性回归
: V/ o' ^: Y5 @) y4 f2 A: C# VLinear trend, 线性趋势
1 e/ I' [! o; I& W3 f' pLoading, 载荷 " K" O& C8 B+ v$ F% R7 {
Location and scale equivariance, 位置尺度同变性$ I2 B* c+ _- G6 l) K, O7 z
Location equivariance, 位置同变性- y5 b% J# _: ]
Location invariance, 位置不变性
$ K. n' u* i2 Q- Z+ GLocation scale family, 位置尺度族% Z( P, I; u! m1 @: E/ P. p8 g
Log rank test, 时序检验
$ O, \$ q: ^) X5 d6 mLogarithmic curve, 对数曲线
( n& G* p; t" Z; g. |# l9 K. Y7 gLogarithmic normal distribution, 对数正态分布2 N( X0 B" b2 ~, a* ]8 t# ~* A1 l0 L
Logarithmic scale, 对数尺度
8 S2 y% c" Y2 M+ d/ eLogarithmic transformation, 对数变换
# Q) O$ { ~' r& ZLogic check, 逻辑检查$ b* Z d* Z1 p9 c9 T
Logistic distribution, 逻辑斯特分布( [9 b$ s3 @& T1 f
Logit transformation, Logit转换6 W+ t j" _0 g# p
LOGLINEAR, 多维列联表通用模型 . I6 v& d1 a# c) m
Lognormal distribution, 对数正态分布% V% N) I% f% o
Lost function, 损失函数
2 V) o' I+ T/ S2 E8 k' W# Q' @+ ]Low correlation, 低度相关8 k6 P! |! f3 U( S
Lower limit, 下限
# m5 z7 a% g# }2 x& mLowest-attained variance, 最小可达方差; G' c9 T" D; @: D
LSD, 最小显著差法的简称
! P3 r$ n/ V; N( `8 lLurking variable, 潜在变量
' k6 f, U5 P& [: z3 e* ~2 H: xMain effect, 主效应; N1 P* ^/ v( @4 C' Y
Major heading, 主辞标目3 _* r: C* a% p! l
Marginal density function, 边缘密度函数4 A- l6 _$ B# i& ^+ _. B
Marginal probability, 边缘概率: n" f2 {5 F5 \: N# ] h
Marginal probability distribution, 边缘概率分布
% |+ C, b/ g" h( c' k4 nMatched data, 配对资料8 g/ T' U- O4 w6 ?) {
Matched distribution, 匹配过分布
) i; r5 s% m9 l" G2 g jMatching of distribution, 分布的匹配2 t/ s8 T1 h0 x* a0 G
Matching of transformation, 变换的匹配- d. t# Z5 l" Q. O( h
Mathematical expectation, 数学期望
3 ~2 G, D s% L( H2 bMathematical model, 数学模型
: t9 R. T; k+ r) O+ r: lMaximum L-estimator, 极大极小L 估计量
( b( L& A5 }6 T' D0 U: M& pMaximum likelihood method, 最大似然法
1 Z! P( |* T9 |! gMean, 均数: S, r* U0 H1 \
Mean squares between groups, 组间均方
3 W2 |7 z3 l; f" m8 h$ z( q. dMean squares within group, 组内均方
8 F; I2 g9 x+ SMeans (Compare means), 均值-均值比较
/ o9 z! r5 }' m/ h( q! gMedian, 中位数" n; p' C2 ~3 j: k4 G3 d
Median effective dose, 半数效量
) K0 m1 B4 o$ C2 i G. GMedian lethal dose, 半数致死量
5 {- o6 T) w' v7 P# t, q7 ]Median polish, 中位数平滑 F7 @" T8 k) w5 f( ]
Median test, 中位数检验- M0 u9 o/ R1 Q% w; O- T* K/ G
Minimal sufficient statistic, 最小充分统计量
, F8 Y( v; x- b/ t( gMinimum distance estimation, 最小距离估计
( R4 `- e9 Q$ c% D eMinimum effective dose, 最小有效量2 e, s6 d$ M* B4 ~
Minimum lethal dose, 最小致死量
" L7 f( Q1 l5 b% |" L) CMinimum variance estimator, 最小方差估计量9 I* u) S" b9 p: g
MINITAB, 统计软件包: }6 h/ s8 B# A) `0 b. v8 P4 k
Minor heading, 宾词标目
6 r t' e" B$ j! ]( V- A9 D- I2 jMissing data, 缺失值
- L7 C* Y$ P) F# vModel specification, 模型的确定
8 I, q. x0 y4 r' T2 Z/ [# EModeling Statistics , 模型统计) h2 [& v& G6 C1 S! c
Models for outliers, 离群值模型
3 X, ^: _6 e5 M, q! x o, kModifying the model, 模型的修正7 q0 W" @+ b' N9 U9 v
Modulus of continuity, 连续性模 _ _0 u) i$ O1 ^1 m! l
Morbidity, 发病率 * b4 w7 @6 I; B! n" u7 e/ K
Most favorable configuration, 最有利构形: |5 n+ c! g+ N: ~* A1 T8 w1 E
Multidimensional Scaling (ASCAL), 多维尺度/多维标度. }5 K4 j) q- N- z' @
Multinomial Logistic Regression , 多项逻辑斯蒂回归
: F8 \! q3 y! A6 {, ?+ cMultiple comparison, 多重比较0 o e3 ]7 O$ b# j7 k1 i
Multiple correlation , 复相关1 @' G/ v7 U9 K8 p/ S- _3 u
Multiple covariance, 多元协方差, Q1 o% h" C4 p- u$ i" l0 M
Multiple linear regression, 多元线性回归6 V, V% \& p% a9 [* B
Multiple response , 多重选项
, \1 t1 U/ _% gMultiple solutions, 多解
& I0 s, `- o/ x; hMultiplication theorem, 乘法定理/ Z1 {% J$ O% y# l4 I6 f
Multiresponse, 多元响应+ L( Y7 l5 b4 \4 F/ v/ Y# O0 E1 v$ ]
Multi-stage sampling, 多阶段抽样; O* E4 ]& q; b: V& A3 `
Multivariate T distribution, 多元T分布2 d. F2 U- c- K8 r& P
Mutual exclusive, 互不相容
9 o- |5 ^* e! G# d+ p5 xMutual independence, 互相独立1 e# N4 C, T" g6 j. |
Natural boundary, 自然边界
% z4 j7 u `! _5 ^4 i! x/ r- tNatural dead, 自然死亡
7 w6 [) V% k. }4 z6 b% R/ q5 WNatural zero, 自然零
9 S" y6 w$ H, x, l& Y' ]Negative correlation, 负相关8 J1 f; V/ J! b o
Negative linear correlation, 负线性相关
9 I; q% Z5 D' S: I& l( \/ [Negatively skewed, 负偏
$ X% z; E( C+ bNewman-Keuls method, q检验! S4 Y+ f0 t! B
NK method, q检验
; d3 c+ n5 s* x/ r: C: _+ s% l! ANo statistical significance, 无统计意义
9 A) r( Z2 j+ C: M4 F( A5 K F$ UNominal variable, 名义变量
4 `) f7 w) N- c: C: gNonconstancy of variability, 变异的非定常性7 T8 S3 T1 g9 ]
Nonlinear regression, 非线性相关
4 W U+ n$ s! L0 a; U% SNonparametric statistics, 非参数统计
4 x# p& J: P7 y8 }* P6 JNonparametric test, 非参数检验, ~/ ~6 I6 M/ F5 c
Nonparametric tests, 非参数检验
! T. I7 d t$ M0 r2 K6 hNormal deviate, 正态离差
3 @4 A6 Y- ?* r9 ^' VNormal distribution, 正态分布
2 v* C: b1 T: Z6 j5 mNormal equation, 正规方程组- |( k' w5 I: {$ x9 Z
Normal ranges, 正常范围
) V0 F! a; e% C/ y$ {( ENormal value, 正常值
! v3 }* H( [+ e8 v( tNuisance parameter, 多余参数/讨厌参数
! X, c+ p9 K) R+ NNull hypothesis, 无效假设
4 x/ k# ^% A' D5 r2 mNumerical variable, 数值变量
5 c+ o0 @8 p# ]6 N: H+ V" ^Objective function, 目标函数
+ y& f6 ?1 }6 U* G+ J% N& @Observation unit, 观察单位 \% A8 [0 c9 L& |; H
Observed value, 观察值7 [+ S" g- H! K% h3 V& F' d: F
One sided test, 单侧检验; [5 \* o; P. t. u0 N7 V
One-way analysis of variance, 单因素方差分析
+ P2 L$ x: c" m3 i& O1 Y2 x' hOneway ANOVA , 单因素方差分析
6 l3 H7 y% x7 t( f6 JOpen sequential trial, 开放型序贯设计
* I5 b4 ^# G/ H" x# l: L: D# tOptrim, 优切尾- [7 V5 J7 G% C6 }; X
Optrim efficiency, 优切尾效率- Q$ |% P& N) X& v% o5 w
Order statistics, 顺序统计量0 m0 I9 R5 ]3 m) W# t
Ordered categories, 有序分类$ @+ C, t; l* ?3 E" D4 q
Ordinal logistic regression , 序数逻辑斯蒂回归
0 b% x# [& j9 \7 r6 S( iOrdinal variable, 有序变量/ D- j% p7 I+ T' ^# A+ l
Orthogonal basis, 正交基% I! q# ]8 H3 l. {% \! m+ Y- M) R
Orthogonal design, 正交试验设计7 [2 p; |' m F* U
Orthogonality conditions, 正交条件3 ~1 ^# a$ ]4 R7 C3 S0 ? [8 ^0 {
ORTHOPLAN, 正交设计 # h2 a) h- U0 ]1 D
Outlier cutoffs, 离群值截断点
6 G. m, x8 ]& O: ?4 ROutliers, 极端值
, n# a$ V! g* xOVERALS , 多组变量的非线性正规相关
( A7 {' j6 [$ H4 y0 k; @4 d+ J9 oOvershoot, 迭代过度
2 A1 `/ q( |" K7 X. \& O* jPaired design, 配对设计0 a% R7 m/ o( W* A3 w0 v! D* r% f; t
Paired sample, 配对样本8 c) ?. Z+ [ |1 z- i J
Pairwise slopes, 成对斜率" k2 H. ^* \1 u; a# J/ A- L
Parabola, 抛物线" y( B7 p+ T, u' p; ~. t* ?
Parallel tests, 平行试验
) ]) Q1 I4 Z4 {1 K9 \5 oParameter, 参数
0 m; H+ O+ O: ?+ L5 g/ C FParametric statistics, 参数统计
4 T) W# }( L2 {7 z8 J1 FParametric test, 参数检验! |2 U. `4 X3 c- B1 W
Partial correlation, 偏相关 z: Z; Z4 d$ J6 a7 o4 o: Q
Partial regression, 偏回归! C* Y9 V5 E9 H& F: T, b) s
Partial sorting, 偏排序6 J2 v: }; H0 @: S8 `! g2 q
Partials residuals, 偏残差
: X6 o( R; ^5 @, ?Pattern, 模式; G5 ^% x( w: K2 v
Pearson curves, 皮尔逊曲线
$ S6 i. V1 m% G+ C4 wPeeling, 退层
% P% Y2 L5 c4 M$ [/ x( J; R$ h9 WPercent bar graph, 百分条形图
. e* q/ p$ m! z/ f- {& \Percentage, 百分比; j) s# Y* Y! K4 V- f4 r# A2 r
Percentile, 百分位数9 L6 N% C3 P' _: U1 i4 |
Percentile curves, 百分位曲线0 B. i& A* U- ?7 P: x
Periodicity, 周期性8 z/ D9 m4 \" T" ~5 j; Y; l
Permutation, 排列
: [5 @0 F+ x1 g& D7 N/ E2 _P-estimator, P估计量
* L: o4 R) Y, r: p5 K/ }Pie graph, 饼图3 ?, r& H0 @3 E: Z
Pitman estimator, 皮特曼估计量( B7 O/ d5 e9 M& b; |
Pivot, 枢轴量
- j, k2 @% A: oPlanar, 平坦
# f: s3 I8 D7 z( A$ `: oPlanar assumption, 平面的假设
2 ?9 W+ O( o/ G( b, }8 CPLANCARDS, 生成试验的计划卡
; {1 }" I" u/ W" A8 ~7 LPoint estimation, 点估计+ \# B5 |7 X- i8 |2 K
Poisson distribution, 泊松分布
& D. R) Z6 C4 _+ r. LPolishing, 平滑, w F! `4 f5 t8 }, {+ @8 V6 ^
Polled standard deviation, 合并标准差0 H+ n5 i, ~7 L
Polled variance, 合并方差
: S: b! K6 o) |# h, Q' L1 `; k( S$ BPolygon, 多边图8 r1 L+ _9 s2 {# Q" ^! z
Polynomial, 多项式& m8 J. ]) Z8 N9 ~
Polynomial curve, 多项式曲线& m; @" A8 W* F1 U
Population, 总体1 H i, p8 ~' }! P
Population attributable risk, 人群归因危险度
?, M. _% d2 S& }% ]! r s& nPositive correlation, 正相关
. ~7 l7 H3 L0 S4 Q) i$ |Positively skewed, 正偏" s) A( y9 M2 J
Posterior distribution, 后验分布6 o' e1 I w& G. |
Power of a test, 检验效能6 W. p" Z0 O* O. v& t* C% T& g
Precision, 精密度
; e3 F9 _2 G! O y1 kPredicted value, 预测值( c& \& }% u4 H+ }/ K5 l" p6 [4 B
Preliminary analysis, 预备性分析
3 U- Q5 h- g7 _( y: kPrincipal component analysis, 主成分分析
" m( f# `* F" Z9 O* g/ }/ U8 K+ H9 KPrior distribution, 先验分布
9 s/ E% F3 ^2 X: v; y) R! }Prior probability, 先验概率. j' a4 v9 K9 W
Probabilistic model, 概率模型
% k' h$ d! g& [# vprobability, 概率
% d0 U4 f& J/ ^( DProbability density, 概率密度& I5 Q, q. E& [( o4 S* f' @( h
Product moment, 乘积矩/协方差
, p+ B. B7 c* O: }8 P0 xProfile trace, 截面迹图2 A* B8 O9 G) v/ l$ D/ i! q$ S6 W4 a
Proportion, 比/构成比* Z' u4 o1 z& n- |* N# \
Proportion allocation in stratified random sampling, 按比例分层随机抽样
; n A& i, @9 t$ M* o" Z, VProportionate, 成比例
H: o$ O0 d2 l0 \Proportionate sub-class numbers, 成比例次级组含量) `4 n0 D! C+ I: B3 m O
Prospective study, 前瞻性调查
5 |, I5 _+ ?0 R( s, pProximities, 亲近性
& w7 g+ b7 W G2 cPseudo F test, 近似F检验
1 W5 ~% ]- b) b0 _. s# YPseudo model, 近似模型7 O3 k# @! Y6 |( ?% C8 d) `
Pseudosigma, 伪标准差2 {) t; T9 R% u
Purposive sampling, 有目的抽样1 s( O: x G$ q ] y9 J, W' h" n% e
QR decomposition, QR分解& f$ N" q5 N7 H+ a V
Quadratic approximation, 二次近似
" |! m1 y5 ^! m. m8 q' m' rQualitative classification, 属性分类, H7 }' s; ?! _- f h- x- g
Qualitative method, 定性方法
7 S- E g4 P1 rQuantile-quantile plot, 分位数-分位数图/Q-Q图, K9 l- Z# ]+ B( j
Quantitative analysis, 定量分析; C! W M l& y3 }. R* N5 w2 _0 ? t
Quartile, 四分位数
- `4 L2 O' R& ~7 k% Z4 eQuick Cluster, 快速聚类
L8 ^3 S2 d$ DRadix sort, 基数排序, S+ k, S. l2 F a' x& |5 |
Random allocation, 随机化分组: S4 d0 @8 t" C, I
Random blocks design, 随机区组设计, X9 c5 u& R5 H g3 y% \. z& W
Random event, 随机事件7 a ~. L7 c+ q2 ^7 a; Y- N
Randomization, 随机化
2 F9 a" m+ S* D1 W. B# GRange, 极差/全距
0 z& d% p2 ?; fRank correlation, 等级相关/ n1 x& D) n/ j2 Q
Rank sum test, 秩和检验
B+ X- ?5 r6 i8 \' ~3 s1 PRank test, 秩检验
+ M; B. N6 C# E8 b8 L% a8 @Ranked data, 等级资料
m& v( q6 f$ a( j% O# zRate, 比率
" d$ N6 b1 K2 M0 O' | yRatio, 比例, {$ B# W3 J* |0 d
Raw data, 原始资料" Q7 c- M, \, h* a# _, |; x. m
Raw residual, 原始残差" O6 D3 i* m" I& O# l+ s; G
Rayleigh's test, 雷氏检验
- [2 f! Z% c. d }$ y I8 P1 o0 nRayleigh's Z, 雷氏Z值 , K' l3 p8 J4 b$ k- X9 x
Reciprocal, 倒数3 {; c y# n0 u# A6 c+ ?
Reciprocal transformation, 倒数变换
/ @, B' X! T" C R9 C" KRecording, 记录+ q, \: B* w4 R, g2 h
Redescending estimators, 回降估计量
% p( n5 P% W: d9 D: F+ ^& h9 rReducing dimensions, 降维
# Q6 v6 x2 T \8 ^Re-expression, 重新表达0 |$ f8 |& o7 u' w6 h
Reference set, 标准组% K- w5 Z# C7 b5 n4 B) M* Q5 u/ d
Region of acceptance, 接受域7 Q" Q$ L; ^+ e8 h* W. Q" f, e
Regression coefficient, 回归系数
7 L9 s6 ?" n2 l9 s# zRegression sum of square, 回归平方和& P y3 I0 {1 w: L {+ ?
Rejection point, 拒绝点
. M" d) k& m9 p( SRelative dispersion, 相对离散度
$ D8 J% n" w0 |4 j# \: ORelative number, 相对数
8 M( B+ C7 E8 M, n' rReliability, 可靠性
: m, ^, S; t8 tReparametrization, 重新设置参数
2 }; G O9 ^' j& \6 {9 ?0 y3 wReplication, 重复
8 E$ x$ ~% z. }1 a1 B- N# M0 aReport Summaries, 报告摘要& s d, z% Z w. a0 Y$ V* P: @
Residual sum of square, 剩余平方和* c/ M1 h6 d; R$ L+ |
Resistance, 耐抗性
4 s8 v5 }! }2 d! M3 E& b1 ~+ cResistant line, 耐抗线
" R% X h6 U* E! Y# ~0 E" u3 qResistant technique, 耐抗技术! X! b( \" R3 i
R-estimator of location, 位置R估计量+ w2 `% Q0 {2 _$ ]2 q
R-estimator of scale, 尺度R估计量
# u: J9 i- S: W* H0 M. R: M8 VRetrospective study, 回顾性调查
; i* T# Z) n; S& _6 @9 z# y" TRidge trace, 岭迹$ V2 n) Y7 x2 j* ?' t7 z8 X5 Q9 E
Ridit analysis, Ridit分析
! M, T0 s# a6 Z) R- i3 ]2 [Rotation, 旋转
4 r6 O1 u# ^* f v6 \2 s5 [2 GRounding, 舍入
: }. G, g& @+ \& p1 [Row, 行
2 M: M r( d9 x: L( |Row effects, 行效应
1 ]# G7 i- B5 ?% P# \$ W7 @, bRow factor, 行因素
7 G8 j7 P ^ G; X' w- T: TRXC table, RXC表' q1 t% |; N: u, i% V
Sample, 样本
. L- B9 g% x# ?- d- hSample regression coefficient, 样本回归系数- B! V0 P% C8 I
Sample size, 样本量! R" N. F0 @" E( X* ~
Sample standard deviation, 样本标准差
% {" b0 `4 t, j8 s! ^Sampling error, 抽样误差' l0 z. }! x+ m( {2 j9 Q& u
SAS(Statistical analysis system ), SAS统计软件包# @0 o/ o$ o) O# H; A! t
Scale, 尺度/量表
8 N6 j2 E0 ]$ [1 B a! ^Scatter diagram, 散点图
0 t8 ~+ k8 m* y: H2 F# ]Schematic plot, 示意图/简图
8 d/ Z: d, p# \1 ^) n. R7 `' WScore test, 计分检验8 ?! t4 x! |/ U) ^* K1 P8 j2 Z8 d( z
Screening, 筛检9 K- O e7 r3 [2 k/ v' h; e
SEASON, 季节分析
" q6 L. Y5 O. o7 G( vSecond derivative, 二阶导数$ P9 F+ s& r5 g5 s# H
Second principal component, 第二主成分
. B3 h5 M8 m6 v9 ^6 N& VSEM (Structural equation modeling), 结构化方程模型 ' w U. H, T: L/ q2 p$ @6 v; C
Semi-logarithmic graph, 半对数图# Y5 O$ k) K. G2 F1 ?! C, f: S; X: ^) d
Semi-logarithmic paper, 半对数格纸
6 m% O5 d! @( R# `! V* kSensitivity curve, 敏感度曲线
+ Y5 s6 I$ y8 J | xSequential analysis, 贯序分析( W( g g' P" G- O
Sequential data set, 顺序数据集
" c5 I4 s, X/ B' s ?! ZSequential design, 贯序设计 K* E- o$ Y( n1 R2 z( B" S. P
Sequential method, 贯序法
$ n2 h, W0 I$ m. bSequential test, 贯序检验法
% w* B0 n0 |& o) fSerial tests, 系列试验
+ _$ g( h% I8 J' |Short-cut method, 简捷法
5 F% g) T C+ Z8 hSigmoid curve, S形曲线/ R Z2 l( @8 R/ p) `7 K9 T2 b
Sign function, 正负号函数
" }6 T+ s7 g2 U3 b- QSign test, 符号检验, V$ J2 y( x$ {4 F) u* Y
Signed rank, 符号秩
+ _9 ^8 Y, Z" M$ ESignificance test, 显著性检验' o( ? Q9 J5 w
Significant figure, 有效数字
, {& p3 z& m8 NSimple cluster sampling, 简单整群抽样
( P$ M3 ~8 z3 {Simple correlation, 简单相关
: e' q6 M, _5 G `1 n+ ~$ F; USimple random sampling, 简单随机抽样
; }; {. y- o/ n9 d: B+ |* eSimple regression, 简单回归' E; v) u% U( Y3 I' ]7 I
simple table, 简单表2 B, S# P2 k) F+ c
Sine estimator, 正弦估计量
b2 V: `3 |& }4 n: V% F7 C1 FSingle-valued estimate, 单值估计5 m$ I. F! u% _- a: p
Singular matrix, 奇异矩阵# W& v( w' v: I
Skewed distribution, 偏斜分布" c2 Q" Y1 [# x, X7 `1 e
Skewness, 偏度$ \; k8 c+ H+ Z/ F$ U
Slash distribution, 斜线分布
% X% `: P+ f/ W$ @0 |4 ?Slope, 斜率* {- Q! T b$ r
Smirnov test, 斯米尔诺夫检验
0 p0 X8 C1 y4 W7 p& q6 ]Source of variation, 变异来源
( R. P" B( U+ c vSpearman rank correlation, 斯皮尔曼等级相关
" D3 d1 `. M- X1 e( vSpecific factor, 特殊因子1 V6 d- l4 R+ F Q% l. ]! i
Specific factor variance, 特殊因子方差
/ J4 Y/ J- d& c; V& T- tSpectra , 频谱
( \4 l r6 l* y, T: V; WSpherical distribution, 球型正态分布
9 i1 @7 [4 c; @: J$ F8 YSpread, 展布$ g- A3 I6 A0 [2 L& B) y' u* p8 D
SPSS(Statistical package for the social science), SPSS统计软件包
: V/ |& t& T. m- bSpurious correlation, 假性相关
+ C- q8 `: Y! m6 ~& qSquare root transformation, 平方根变换 j1 B% d) v9 w( ~
Stabilizing variance, 稳定方差# t" S8 O' G! F$ A8 y6 F$ Y
Standard deviation, 标准差9 t C K$ t3 \ Z
Standard error, 标准误
" u8 k5 C) i2 Y- Q: }$ S$ w6 Q2 kStandard error of difference, 差别的标准误4 J; J& x( M7 L1 Q5 H8 f- M3 |2 }
Standard error of estimate, 标准估计误差
+ y/ g2 L. ]! Y9 `# N' IStandard error of rate, 率的标准误' E/ T6 c5 \- i1 _8 Q9 t
Standard normal distribution, 标准正态分布9 V8 i$ B" K" q C- M- O
Standardization, 标准化 L) I5 o6 t! \5 j
Starting value, 起始值
: P1 G$ u* S& q7 @Statistic, 统计量
# T5 `0 p4 x9 d* g' } tStatistical control, 统计控制
2 _" Z$ B8 S7 |; ]. k# P. RStatistical graph, 统计图4 Q" ~4 j: ~$ d; f$ Q4 i; D
Statistical inference, 统计推断
& f1 F% C2 i+ L7 @. W- O2 _$ KStatistical table, 统计表0 V. s( e0 f, C! c6 X% H6 ]' j
Steepest descent, 最速下降法
t' e* w7 y3 O' c; qStem and leaf display, 茎叶图
& L- z5 |" g$ k4 ^Step factor, 步长因子3 _& p* G- a( e1 V6 b% q
Stepwise regression, 逐步回归
, B6 N6 p! C, f- e! ]6 D) u4 WStorage, 存
- M9 Z0 v4 S" O! a0 aStrata, 层（复数）7 s" A+ b0 v% K; t2 _. c
Stratified sampling, 分层抽样3 } Z) g; U* x( ?" O8 {
Stratified sampling, 分层抽样7 B% V8 g! s' m! ^
Strength, 强度5 S5 W" W) @5 v4 k
Stringency, 严密性
3 D) @, R' G' K* k' G9 XStructural relationship, 结构关系
" h0 v8 G* ^, F* x. Q) yStudentized residual, 学生化残差/t化残差0 `% R [4 D m) b" ~
Sub-class numbers, 次级组含量; p$ W6 B1 [3 J
Subdividing, 分割
! l, c! J1 m( X @# ASufficient statistic, 充分统计量& Q4 L: }3 d+ q/ N/ D
Sum of products, 积和: Z7 k- S9 s1 c! Z2 h
Sum of squares, 离差平方和0 t( \' Z6 b) U9 R7 W _* Z. {- O
Sum of squares about regression, 回归平方和
3 J% M' |9 w+ v: J( ~Sum of squares between groups, 组间平方和
; _( ]/ o1 O4 ^+ m. @9 _1 W) n1 ^Sum of squares of partial regression, 偏回归平方和
8 E$ {9 ^4 l2 w- `6 k" nSure event, 必然事件; f, ^, f ?" Y8 b+ {5 ^% V" ]- v
Survey, 调查4 ~& [9 E* X) [+ G
Survival, 生存分析
7 D9 `- F: N- T" q( O: hSurvival rate, 生存率) o) {1 R4 b; N
Suspended root gram, 悬吊根图
7 g1 ? v$ h0 K0 `2 J# q$ F8 c3 L( ?$ c8 XSymmetry, 对称1 }! A c4 _7 U" W% ?9 w. n
Systematic error, 系统误差
& @8 t# b- B- b5 [3 D6 v, FSystematic sampling, 系统抽样6 k3 S6 [# I' d7 P1 K) c/ S
Tags, 标签
w! o- v6 O2 S+ T. b% kTail area, 尾部面积
! @, l$ d: q) b0 e$ Z$ Y- nTail length, 尾长
$ W4 P7 s5 D# Q7 `0 p7 o l5 _Tail weight, 尾重4 F8 L* P1 S5 g: m( e6 R. y
Tangent line, 切线! W2 @# V! Q' c, f7 e
Target distribution, 目标分布
8 ?7 `6 q# H; h7 B, E; @/ o pTaylor series, 泰勒级数( S2 W! a( t7 [; I# [* U' D7 Y
Tendency of dispersion, 离散趋势
3 x" _8 \0 o. y9 kTesting of hypotheses, 假设检验
2 T" g, @2 g1 ^% TTheoretical frequency, 理论频数
8 b7 I& P. I1 XTime series, 时间序列
) l$ U0 ^% Q+ ~( ^Tolerance interval, 容忍区间
0 I0 @ ]! U# J- bTolerance lower limit, 容忍下限
7 R/ s* d/ H7 l4 [! F/ }. @' XTolerance upper limit, 容忍上限, c6 o9 W7 a# p: Z
Torsion, 扰率, S& e4 [" O1 @3 c+ ]% t) c' J( T ?
Total sum of square, 总平方和/ z m! \9 y# q! }/ m/ j
Total variation, 总变异
7 y P& _+ {" HTransformation, 转换: h4 n1 I8 c. _' X
Treatment, 处理
) G& e7 s6 u0 f$ }: a" q$ gTrend, 趋势
! n- g7 r2 }" S6 ]3 a- j! ETrend of percentage, 百分比趋势) s* D1 R, X c- k" D
Trial, 试验6 J# b2 q4 t3 ~5 s' D$ T
Trial and error method, 试错法
; d6 A) S6 ^; STuning constant, 细调常数% [2 _. z& w Q' r g4 R4 j
Two sided test, 双向检验2 n8 B% n5 x9 T6 l& J1 k+ R3 k
Two-stage least squares, 二阶最小平方/ A- T" K5 X1 k6 O7 ~
Two-stage sampling, 二阶段抽样
+ g0 n" I$ C& s7 A% O" nTwo-tailed test, 双侧检验6 k j% T0 ]2 L( B: B- g9 l1 K
Two-way analysis of variance, 双因素方差分析8 R- ?( o# ^/ p2 q& `" f( b5 S, D
Two-way table, 双向表! S" g. Z$ m* e9 `- A
Type I error, 一类错误/α错误3 ]+ ~; A: W3 g
Type II error, 二类错误/β错误0 B, Z( b3 U* Y) l
UMVU, 方差一致最小无偏估计简称
" t5 b3 }2 p" N& ]/ S1 LUnbiased estimate, 无偏估计5 |( f1 J6 i2 k5 Z3 L, `
Unconstrained nonlinear regression , 无约束非线性回归
) x) |- R, o/ V \" Q2 MUnequal subclass number, 不等次级组含量
0 f7 D/ h+ H- A: ?; r dUngrouped data, 不分组资料: K, n& a+ ^$ k
Uniform coordinate, 均匀坐标
; h* C, ]1 a; X9 Z3 J7 m& j {Uniform distribution, 均匀分布
+ I" R& W/ Y) h7 ~* m+ TUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
" d7 v3 k1 A% a& W) C* x' G" |& }Unit, 单元
! ?" Q y# M# c7 CUnordered categories, 无序分类
' e9 n! a8 D! k0 c2 FUpper limit, 上限; l8 N& R8 f3 ?2 T0 j
Upward rank, 升秩
r& n' o p) {- eVague concept, 模糊概念- D- ? k: H" T6 I+ t$ U
Validity, 有效性1 m+ n! ~6 E0 V- R; h, |
VARCOMP (Variance component estimation), 方差元素估计
, e6 N" c# b) G6 xVariability, 变异性
1 m- C) A g; MVariable, 变量
3 S" W7 S4 P9 K- F/ R, m* o$ r1 y) WVariance, 方差
4 j! v) Z" b# I+ d! N9 N. PVariation, 变异8 U4 s' W/ ?7 E. |7 @
Varimax orthogonal rotation, 方差最大正交旋转5 |; F2 K) E8 \- v2 I) Q# \
Volume of distribution, 容积
# C7 L/ r- p7 M, v. iW test, W检验
( v& `4 k* m+ pWeibull distribution, 威布尔分布
: Q* M& F2 _6 @/ fWeight, 权数8 O( p/ B, q9 k) W
Weighted Chi-square test, 加权卡方检验/Cochran检验( w0 D+ B! G2 C0 `
Weighted linear regression method, 加权直线回归
2 }. |% P$ @ y {! N% ]1 PWeighted mean, 加权平均数
2 i/ K; r% @7 x6 qWeighted mean square, 加权平均方差- F# t' k$ w# `3 j
Weighted sum of square, 加权平方和$ K' g# S5 p" y/ d8 B2 l
Weighting coefficient, 权重系数
# p8 K, s8 y4 J' t, ^Weighting method, 加权法
6 e; A0 P, ~* `1 ~/ HW-estimation, W估计量
) ]! @3 s5 n9 Q. `& F; a& p. d t. YW-estimation of location, 位置W估计量
+ C1 F. w8 {- ~# g0 a+ v8 N4 {. ~Width, 宽度! y0 |( G3 h7 [& }
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验# [3 _1 p4 M/ N$ f) q0 N
Wild point, 野点/狂点
7 O) W* s, k) q9 QWild value, 野值/狂值
9 a$ k+ J) b& P, L2 U) b# ?Winsorized mean, 缩尾均值5 u- h7 ?& n: f
Withdraw, 失访 ?4 F2 X% D) S- @' O5 y6 \
Youden's index, 尤登指数1 I& T; E$ R3 G4 D0 T
Z test, Z检验' l Y4 c+ [) K
Zero correlation, 零相关; { d" ]6 O7 O' }8 |
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
